Knowledge Graphs (KGs) such as Freebase [1]}, DBpedia [2]}, and Wikidata [3]} have been created in order to share linked data which describes entities and the relationships between them. The availability of these various cross-domain KGs has sparked interest in undertaking research directions such as KG completion using tasks like link prediction. Hence, different Knowledge Graph Embedding (KGE) approaches, which map KGs to a low dimensional vector space, based on a link prediction task have been published. Link prediction is widely used because in the Open World Assumption the knowledge explicitly represented in a KG is never complete, there are always missing facts which can be predicted using link prediction.
